Application of adaptive filters to noninvasive acoustical detection of coronary occlusions before and after angioplasty

Isolated diastolic heart sounds taken from recordings made at the patient´s bedside were modeled using the autoregressive (AR) and autoregressive moving average (ARMA) methods after adaptive line enhancement (ALE). Decisions were made in a blind fashion without prior knowledge of whether a given recording was made before or after angioplasty. Resulting model frequency spectra showed greater high frequency components (between 400 and 800 Hz) in preangioplasty patients, and a consistent shift in amplitude of the second pole pairs of the AR and ARMA methods with surgery. Blind assessment based on frequency spectra and poles, correctly classified the diastolic recordings in 18 of 20 cases. These results provide evidence supporting the hypothesis that coronary stenoses produce detectable sounds during diastole.